A Response to Punya Mishra on AI and Creativity
My friend and colleague Dr. Punya Mishra recently gave a talk on generative AI and creativity that was full of insight, humor, and challenge. You can always count on Punya to make you laugh and think at the same time—and this talk was no exception.
He described generative AI as a “smart, drunk, biased, and supremely confident intern,” which might be the most accurate (and entertaining) description I’ve heard yet. He also shared inspiring examples of using AI to create poems, music, interactive simulations, and visual art—most of which he had no technical background to build from scratch.
His point was clear: when accuracy doesn’t matter, and when we come to AI as curious, creative teachers and designers, something genuinely exciting can happen.
But as I listened, I also found myself wondering about some deeper and maybe less comfortable questions—questions that I think we, as educators and designers, need to be asking ourselves more often.
1. Are We Outsourcing Emotional Labor?
Punya noted a recent trend: users increasingly turning to AI not for ideas, but for therapy and companionship. In fact, “companionship” has now surpassed “idea generation” as the top reason people use chatbots like ChatGPT.
That gives me pause.
Are we outsourcing our need to be heard and known to something that can only mimic understanding? What does that do to our capacity for genuine human connection, especially for young people already navigating digital saturation and identity formation?
Is AI becoming not just a tool but a substitute relationship?
2. What Kind of Creativity Are We Valuing?
Punya showed how AI can help us make things—quickly, beautifully, and in many styles. But I wonder if that ease could quietly reshape our definition of creativity itself.
Are we drifting toward creative outputs that machines are good at—things with recognizable form, familiar rhythm, predictable elegance?
What about the messy, uncertain, deeply human kinds of creativity that resist polish and take time? Do we risk optimizing for style over substance?
3. What Happens When AI Becomes Our Co-Teacher?
Many educators are now using AI for lesson planning, quiz generation, grading, and feedback. On the surface, that sounds efficient. But efficiency can be a trap.
If AI takes over the design work, what happens to our joy in teaching? Our intellectual ownership? Our sense of craft?
Do we begin to devalue deep reflection and slow pedagogical thinking simply because the “intern” is always ready with a faster answer?
4. Who Gets Left Out of This Future?
It’s easy to celebrate these tools when you’re a well-resourced, tech-savvy, curious educator. But not everyone has the time, bandwidth, or institutional support to explore AI in this way.
Whose voices are reinforced by AI, and whose are distorted or erased? What cultural assumptions are baked into the systems we’re now treating as co-authors and collaborators?
If we don’t wrestle with those questions, are we just building another layer of inequality into education?
5. What Should Never Be Automated?
Here’s the questions I keep returning to:
What if the real danger isn’t the tool—but the logic behind it?
The idea that everything complex should be made frictionless?
As someone who works in the world of learning experience design, I spend much of my time helping people navigate ambiguity, uncertainty, and growth. These are not processes we should automate. These are deeply human experiences we need to protect.
Punya’s talk reminded me of what’s possible. This response is a way of holding space for what’s at stake.
Let’s keep building with these tools. But let’s also keep asking the harder questions.
Not because we’re afraid of AI.
But because we care about what it means to be fully human.
